Journal article 566 views 111 downloads
Practical machine learning for disease diagnosis
Cell Reports Methods, Volume: 1, Issue: 6, Start page: 100103
Swansea University Author:
Huw Summers
-
PDF | Version of Record
Copyright: 2021 The Author(s). This is an open access article under the CC BY-NC-ND license
Download (416.8KB)
DOI (Published version): 10.1016/j.crmeth.2021.100103
Abstract
Deep learning neural networks are a powerful tool in the analytical toolbox of modern microscopy, but they come with an exacting requirement for accurately annotated, ground truth cell images. Otesteanu et al. (2021) elegantly streamline this process, implementing network training by using patient-l...
| Published in: | Cell Reports Methods |
|---|---|
| ISSN: | 2667-2375 |
| Published: |
Elsevier BV
2021
|
| Online Access: |
Check full text
|
| URI: | https://cronfa.swan.ac.uk/Record/cronfa58659 |
| Abstract: |
Deep learning neural networks are a powerful tool in the analytical toolbox of modern microscopy, but they come with an exacting requirement for accurately annotated, ground truth cell images. Otesteanu et al. (2021) elegantly streamline this process, implementing network training by using patient-level rather than cell-level disease classification. |
|---|---|
| College: |
Faculty of Science and Engineering |
| Issue: |
6 |
| Start Page: |
100103 |